Chunking In Manipuri Using CRF
نویسندگان
چکیده
منابع مشابه
Manipuri Chunking: An Incremental Model with POS and RMWE
This paper records the work of Manipuri Chunking by using the commonly use tool of Support Vector Machine (SVM). Manipur being a very highly agglutinative language have to be careful in selecting the features for running the SVM. An experiment is being performed with 35,000 words to check whether the POS tagged and the Reduplicated Multiword Expression (RMWE) can improve the Chunk identificatio...
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In this paper we propose an approach to Part of Speech (PoS) tagging using a combination of Hidden Markov Model and error driven learning. For the NLPAI joint task, we also implement a chunker using Conditional Random Fields (CRFs). The results for the PoS tagging and chunking task are separately reported along with the results of the joint task.
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This paper deals with the identification of Multiword Expressions (MWEs) in Manipuri, a highly agglutinative Indian Language. Manipuri is listed in the Eight Schedule of Indian Constitution. MWE plays an important role in the applications of Natural Language Processing(NLP) like Machine Translation, Part of Speech tagging, Information Retrieval, Question Answering etc. Feature selection is an i...
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This paper gives a detail overview about the modified features selection in CRF (Conditional Random Field) based Manipuri POS (Part of Speech) tagging. Selection of features is so important in CRF that the better are the features then the better are the outputs. This work is an attempt or an experiment to make the previous work more efficient. Multiple new features are tried to run the CRF and ...
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ژورنال
عنوان ژورنال: International Journal on Natural Language Computing
سال: 2014
ISSN: 2319-4111,2278-1307
DOI: 10.5121/ijnlc.2014.3312